Cellular communication systems supporting mobile communications have become ubiquitous and in particular second generation cellular communication systems such as the Global System for Mobile Communication (GSM) and third Generation cellular communication systems such as the Universal Mobile Telecommunication System (UMTS) have become widespread.
In order to provide improved communication services and increased efficiency, cellular communication systems are continuously developed and enhanced. For example, currently, the 3rd Generation Partnership Project (3GPP) standards body is in the process of standardising improvements to GSM and UMTS known as Long Term Evolution (LTE).
In comparison to systems such as GSM and UMTS, LTE employs an architecture wherein the base stations (also referred to as evolved Node Bs (eNBs)) comprise more functionality. For example, the eNBs tend to be responsible for many functions associated with the air interface resource control and management including for example admission control, handover management etc. For example, the eNBs of LTE are responsible for many of the functions that are performed by a Base Station Controller (BSC) of a GSM system or a Radio Network Controller (RNC) of a UMTS system.
In LTE, a simpler network architecture tends to be used wherein the eNBs are directly coupled to core network elements. Furthermore, for LTE, the user plane (user data traffic) and control plane (for control data signaling) are treated separately. Specifically, the eNBs are coupled to Serving Gateways of the Core Network for supporting the user plane and to a Mobile Management Entity (MME) for supporting the control plane.
The MME provides functionality for managing the mobility of the user equipments including for example keeping track of the location of the user equipment, changing Serving Gateways, MME handovers, paging etc.
However, a problem in many LTE systems and scenarios is that MMEs may be overloaded. For example, the signaling required to support the user equipments registered with an MME may exceed the bandwidth of the MME's interfaces or the processing required may exceed the available computational or memory resource.
In order to address MME overloading, different solutions have been proposed. However, these tend to be suboptimal and have associated disadvantages.
Specifically, it has been proposed that static capacity information for the available MMEs may be stored in the eNBs and used by the eNB when selecting MMEs. However, although this may improve the load distribution, it tends to be inflexible and is incapable of dynamically adjusting the load distribution to the specific conditions experienced. Thus, whereas it may allow statistical averaging, it does not avoid or react to overload conditions.
It has also been proposed to broadcast overload conditions to all eNBs when an MME is overloaded. However, this tends to be suboptimal as eNBs typically cannot take significant short term remedial action that can resolve the overload situation quickly. This is due to the fact that MME (re)selection is only possible at specific events such as on attachment or for some MME handovers. Thus, the approach tends to be inflexible and provide insufficient load correction. Furthermore, it may further increase the loading of the MME at a time when this is already overloaded as it needs to communicate the overloading to the eNBs.
It has also been proposed that the MMEs broadcast continuous load indicators to the eNBs. However, whereas this may dynamically adapt and improve the load distribution between MMEs, it also increases the loading of the MMEs as frequent load indications need to be transmitted. It furthermore uses significant bandwidth and complicates processing at the MME and eNBs.
Hence, an improved system would be advantageous and in particular a system allowing increased flexibility, improved MME load distribution, facilitated operation, facilitated implementation and/or improved performance would be advantageous.